Create an Asynchronous Multi-Model Quantura Forecast Job

POST

ensemble-forecasts

curl --request POST \
  --url https://quantura.studio/api/v1/ensemble-forecasts \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "prediction_length": 30,
  "quantiles": [
    123
  ],
  "models": {},
  "source": {
    "type": "ticker",
    "symbol": "<string>",
    "price_side": "bid",
    "start": "2023-12-25",
    "limit": 500,
    "frequency": "1Day",
    "adjustment": "raw",
    "session": "regular"
  },
  "transform": "auto",
  "context_length": 512,
  "model_failure_policy": "fail",
  "frequency": "1D",
  "calendar": "NYSE",
  "workspace_id": "<string>",
  "analytics_context": {
    "analytics_consent": "granted",
    "client_id": "<string>",
    "session_id": 123,
    "consent_at": "2023-11-07T05:31:56Z"
  },
  "history_lag_minutes": 0,
  "toto_variant": "4m",
  "history_cutoff_at": "2023-11-07T05:31:56Z",
  "prediction_end_at": "2023-11-07T05:31:56Z",
  "analysis_mode": "forecast"
}
'

import requests

url = "https://quantura.studio/api/v1/ensemble-forecasts"

payload = {
    "prediction_length": 30,
    "quantiles": [123],
    "models": {},
    "source": {
        "type": "ticker",
        "symbol": "<string>",
        "price_side": "bid",
        "start": "2023-12-25",
        "limit": 500,
        "frequency": "1Day",
        "adjustment": "raw",
        "session": "regular"
    },
    "transform": "auto",
    "context_length": 512,
    "model_failure_policy": "fail",
    "frequency": "1D",
    "calendar": "NYSE",
    "workspace_id": "<string>",
    "analytics_context": {
        "analytics_consent": "granted",
        "client_id": "<string>",
        "session_id": 123,
        "consent_at": "2023-11-07T05:31:56Z"
    },
    "history_lag_minutes": 0,
    "toto_variant": "4m",
    "history_cutoff_at": "2023-11-07T05:31:56Z",
    "prediction_end_at": "2023-11-07T05:31:56Z",
    "analysis_mode": "forecast"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    prediction_length: 30,
    quantiles: [123],
    models: {},
    source: {
      type: 'ticker',
      symbol: '<string>',
      price_side: 'bid',
      start: '2023-12-25',
      limit: 500,
      frequency: '1Day',
      adjustment: 'raw',
      session: 'regular'
    },
    transform: 'auto',
    context_length: 512,
    model_failure_policy: 'fail',
    frequency: '1D',
    calendar: 'NYSE',
    workspace_id: '<string>',
    analytics_context: {
      analytics_consent: 'granted',
      client_id: '<string>',
      session_id: 123,
      consent_at: '2023-11-07T05:31:56Z'
    },
    history_lag_minutes: 0,
    toto_variant: '4m',
    history_cutoff_at: '2023-11-07T05:31:56Z',
    prediction_end_at: '2023-11-07T05:31:56Z',
    analysis_mode: 'forecast'
  })
};

fetch('https://quantura.studio/api/v1/ensemble-forecasts', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://quantura.studio/api/v1/ensemble-forecasts",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'prediction_length' => 30,
    'quantiles' => [
        123
    ],
    'models' => [
        
    ],
    'source' => [
        'type' => 'ticker',
        'symbol' => '<string>',
        'price_side' => 'bid',
        'start' => '2023-12-25',
        'limit' => 500,
        'frequency' => '1Day',
        'adjustment' => 'raw',
        'session' => 'regular'
    ],
    'transform' => 'auto',
    'context_length' => 512,
    'model_failure_policy' => 'fail',
    'frequency' => '1D',
    'calendar' => 'NYSE',
    'workspace_id' => '<string>',
    'analytics_context' => [
        'analytics_consent' => 'granted',
        'client_id' => '<string>',
        'session_id' => 123,
        'consent_at' => '2023-11-07T05:31:56Z'
    ],
    'history_lag_minutes' => 0,
    'toto_variant' => '4m',
    'history_cutoff_at' => '2023-11-07T05:31:56Z',
    'prediction_end_at' => '2023-11-07T05:31:56Z',
    'analysis_mode' => 'forecast'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://quantura.studio/api/v1/ensemble-forecasts"

	payload := strings.NewReader("{\n  \"prediction_length\": 30,\n  \"quantiles\": [\n    123\n  ],\n  \"models\": {},\n  \"source\": {\n    \"type\": \"ticker\",\n    \"symbol\": \"<string>\",\n    \"price_side\": \"bid\",\n    \"start\": \"2023-12-25\",\n    \"limit\": 500,\n    \"frequency\": \"1Day\",\n    \"adjustment\": \"raw\",\n    \"session\": \"regular\"\n  },\n  \"transform\": \"auto\",\n  \"context_length\": 512,\n  \"model_failure_policy\": \"fail\",\n  \"frequency\": \"1D\",\n  \"calendar\": \"NYSE\",\n  \"workspace_id\": \"<string>\",\n  \"analytics_context\": {\n    \"analytics_consent\": \"granted\",\n    \"client_id\": \"<string>\",\n    \"session_id\": 123,\n    \"consent_at\": \"2023-11-07T05:31:56Z\"\n  },\n  \"history_lag_minutes\": 0,\n  \"toto_variant\": \"4m\",\n  \"history_cutoff_at\": \"2023-11-07T05:31:56Z\",\n  \"prediction_end_at\": \"2023-11-07T05:31:56Z\",\n  \"analysis_mode\": \"forecast\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://quantura.studio/api/v1/ensemble-forecasts")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"prediction_length\": 30,\n  \"quantiles\": [\n    123\n  ],\n  \"models\": {},\n  \"source\": {\n    \"type\": \"ticker\",\n    \"symbol\": \"<string>\",\n    \"price_side\": \"bid\",\n    \"start\": \"2023-12-25\",\n    \"limit\": 500,\n    \"frequency\": \"1Day\",\n    \"adjustment\": \"raw\",\n    \"session\": \"regular\"\n  },\n  \"transform\": \"auto\",\n  \"context_length\": 512,\n  \"model_failure_policy\": \"fail\",\n  \"frequency\": \"1D\",\n  \"calendar\": \"NYSE\",\n  \"workspace_id\": \"<string>\",\n  \"analytics_context\": {\n    \"analytics_consent\": \"granted\",\n    \"client_id\": \"<string>\",\n    \"session_id\": 123,\n    \"consent_at\": \"2023-11-07T05:31:56Z\"\n  },\n  \"history_lag_minutes\": 0,\n  \"toto_variant\": \"4m\",\n  \"history_cutoff_at\": \"2023-11-07T05:31:56Z\",\n  \"prediction_end_at\": \"2023-11-07T05:31:56Z\",\n  \"analysis_mode\": \"forecast\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://quantura.studio/api/v1/ensemble-forecasts")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"prediction_length\": 30,\n  \"quantiles\": [\n    123\n  ],\n  \"models\": {},\n  \"source\": {\n    \"type\": \"ticker\",\n    \"symbol\": \"<string>\",\n    \"price_side\": \"bid\",\n    \"start\": \"2023-12-25\",\n    \"limit\": 500,\n    \"frequency\": \"1Day\",\n    \"adjustment\": \"raw\",\n    \"session\": \"regular\"\n  },\n  \"transform\": \"auto\",\n  \"context_length\": 512,\n  \"model_failure_policy\": \"fail\",\n  \"frequency\": \"1D\",\n  \"calendar\": \"NYSE\",\n  \"workspace_id\": \"<string>\",\n  \"analytics_context\": {\n    \"analytics_consent\": \"granted\",\n    \"client_id\": \"<string>\",\n    \"session_id\": 123,\n    \"consent_at\": \"2023-11-07T05:31:56Z\"\n  },\n  \"history_lag_minutes\": 0,\n  \"toto_variant\": \"4m\",\n  \"history_cutoff_at\": \"2023-11-07T05:31:56Z\",\n  \"prediction_end_at\": \"2023-11-07T05:31:56Z\",\n  \"analysis_mode\": \"forecast\"\n}"

response = http.request(request)
puts response.read_body

{
  "data": {
    "forecast_id": "ens_01JEXAMPLE7M6N",
    "status": "queued",
    "progress": {
      "completed_models": 0,
      "total_models": 4,
      "current_model": null
    },
    "status_url": "/api/v1/ensemble-forecasts/ens_01JEXAMPLE7M6N",
    "result_url": "/api/v1/ensemble-forecasts/ens_01JEXAMPLE7M6N"
  },
  "meta": {
    "api_version": "v1"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Headers

Idempotency-Key

string

Replays the same normalized request without launching duplicate compute.

Maximum string length: 180

Body

application/json

prediction_length

integer

default:30

required

Required range: 1 <= x <= 512

horizon_mode

enum<string>

required

Available options:

trading_sessions,

calendar_days,

frequency_periods

quantiles

number[]

required

Required array length: 1 - 21 elements

models

object

required

Show child attributes

source

object

required

Option 1
Option 2
Option 3
Option 4
Option 5

Show child attributes

transform

enum<string>

default:auto

Prediction-market sources enforce bounded logit forecasting, with epsilon 1e-6 at transform boundaries.

Available options:

auto,

log,

none,

logit

context_length

integer | null

default:512

Required range: 40 <= x <= 16384

model_failure_policy

enum<string>

default:fail

Available options:

fail,

renormalize

frequency

string

default:1D

Canonical market intervals: 1min, 5min, 15min, 30min, 1h, 4h, 1D, 1W-MON, 1MS. source.frequency determines market input bars; series/workspace datasets can also use validated pandas offsets.

calendar

string

default:NYSE

workspace_id

string

analytics_context

object

Optional consented website telemetry; sanitized separately from model configuration and excluded from cache identity. Invalid or unavailable telemetry does not block forecasting.

Show child attributes

history_lag_minutes

integer

default:0

Input cutoff before request time, in minutes (hours × 60; days × 1440). Select up to 500 observations BEFORE cutoff. Source retention still applies. No fixed 90-day cutoff-age cap: 120 days is 172800 minutes; 180 days is 259200 minutes. Availability depends on provider retention. Positive values create a historical replay, not a previously published forecast. Later observations are separate overlays.

Required range: x >= 0

toto_variant

enum<string>

default:4m

Approved Toto size, smallest to largest. Only relevant when Toto is enabled. The server pins the checkpoint and revision, including in the cache identity; clients cannot submit arbitrary model repositories. All sizes require at least 32 observed values.

Available options:

4m,

22m,

313m,

1b,

2.5b

history_cutoff_at

string<date-time>

Optional past absolute cutoff with timezone offset (ISO 8601), subject to available source history. Cannot be combined with a positive history_lag_minutes. Browser calendar values convert from the user's device timezone to UTC.

prediction_end_at

string<date-time>

Optional absolute end date/time. After input materialization, the server derives the number of forecast bars only for completed future interval boundaries through this time (never rounded past the requested end), still subject to 512 and model-specific limits. NYSE daily forecasts use real exchange sessions in the selected calendar window. Overrides prediction_length.

analysis_mode

enum<string>

default:forecast

New jobs provide forecast quantiles without buy/sell classifications. Historical saved jobs remain readable.

Available options:

forecast

Response

Forecast job queued.

data

object

required

Show child attributes

meta

object

required

Show child attributes

Create an Asynchronous Multi-Model Quantura Forecast Job

curl --request POST \
  --url https://quantura.studio/api/v1/ensemble-forecasts \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "prediction_length": 30,
  "quantiles": [
    123
  ],
  "models": {},
  "source": {
    "type": "ticker",
    "symbol": "<string>",
    "price_side": "bid",
    "start": "2023-12-25",
    "limit": 500,
    "frequency": "1Day",
    "adjustment": "raw",
    "session": "regular"
  },
  "transform": "auto",
  "context_length": 512,
  "model_failure_policy": "fail",
  "frequency": "1D",
  "calendar": "NYSE",
  "workspace_id": "<string>",
  "analytics_context": {
    "analytics_consent": "granted",
    "client_id": "<string>",
    "session_id": 123,
    "consent_at": "2023-11-07T05:31:56Z"
  },
  "history_lag_minutes": 0,
  "toto_variant": "4m",
  "history_cutoff_at": "2023-11-07T05:31:56Z",
  "prediction_end_at": "2023-11-07T05:31:56Z",
  "analysis_mode": "forecast"
}
'

import requests

url = "https://quantura.studio/api/v1/ensemble-forecasts"

payload = {
    "prediction_length": 30,
    "quantiles": [123],
    "models": {},
    "source": {
        "type": "ticker",
        "symbol": "<string>",
        "price_side": "bid",
        "start": "2023-12-25",
        "limit": 500,
        "frequency": "1Day",
        "adjustment": "raw",
        "session": "regular"
    },
    "transform": "auto",
    "context_length": 512,
    "model_failure_policy": "fail",
    "frequency": "1D",
    "calendar": "NYSE",
    "workspace_id": "<string>",
    "analytics_context": {
        "analytics_consent": "granted",
        "client_id": "<string>",
        "session_id": 123,
        "consent_at": "2023-11-07T05:31:56Z"
    },
    "history_lag_minutes": 0,
    "toto_variant": "4m",
    "history_cutoff_at": "2023-11-07T05:31:56Z",
    "prediction_end_at": "2023-11-07T05:31:56Z",
    "analysis_mode": "forecast"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    prediction_length: 30,
    quantiles: [123],
    models: {},
    source: {
      type: 'ticker',
      symbol: '<string>',
      price_side: 'bid',
      start: '2023-12-25',
      limit: 500,
      frequency: '1Day',
      adjustment: 'raw',
      session: 'regular'
    },
    transform: 'auto',
    context_length: 512,
    model_failure_policy: 'fail',
    frequency: '1D',
    calendar: 'NYSE',
    workspace_id: '<string>',
    analytics_context: {
      analytics_consent: 'granted',
      client_id: '<string>',
      session_id: 123,
      consent_at: '2023-11-07T05:31:56Z'
    },
    history_lag_minutes: 0,
    toto_variant: '4m',
    history_cutoff_at: '2023-11-07T05:31:56Z',
    prediction_end_at: '2023-11-07T05:31:56Z',
    analysis_mode: 'forecast'
  })
};

fetch('https://quantura.studio/api/v1/ensemble-forecasts', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://quantura.studio/api/v1/ensemble-forecasts",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'prediction_length' => 30,
    'quantiles' => [
        123
    ],
    'models' => [
        
    ],
    'source' => [
        'type' => 'ticker',
        'symbol' => '<string>',
        'price_side' => 'bid',
        'start' => '2023-12-25',
        'limit' => 500,
        'frequency' => '1Day',
        'adjustment' => 'raw',
        'session' => 'regular'
    ],
    'transform' => 'auto',
    'context_length' => 512,
    'model_failure_policy' => 'fail',
    'frequency' => '1D',
    'calendar' => 'NYSE',
    'workspace_id' => '<string>',
    'analytics_context' => [
        'analytics_consent' => 'granted',
        'client_id' => '<string>',
        'session_id' => 123,
        'consent_at' => '2023-11-07T05:31:56Z'
    ],
    'history_lag_minutes' => 0,
    'toto_variant' => '4m',
    'history_cutoff_at' => '2023-11-07T05:31:56Z',
    'prediction_end_at' => '2023-11-07T05:31:56Z',
    'analysis_mode' => 'forecast'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://quantura.studio/api/v1/ensemble-forecasts"

	payload := strings.NewReader("{\n  \"prediction_length\": 30,\n  \"quantiles\": [\n    123\n  ],\n  \"models\": {},\n  \"source\": {\n    \"type\": \"ticker\",\n    \"symbol\": \"<string>\",\n    \"price_side\": \"bid\",\n    \"start\": \"2023-12-25\",\n    \"limit\": 500,\n    \"frequency\": \"1Day\",\n    \"adjustment\": \"raw\",\n    \"session\": \"regular\"\n  },\n  \"transform\": \"auto\",\n  \"context_length\": 512,\n  \"model_failure_policy\": \"fail\",\n  \"frequency\": \"1D\",\n  \"calendar\": \"NYSE\",\n  \"workspace_id\": \"<string>\",\n  \"analytics_context\": {\n    \"analytics_consent\": \"granted\",\n    \"client_id\": \"<string>\",\n    \"session_id\": 123,\n    \"consent_at\": \"2023-11-07T05:31:56Z\"\n  },\n  \"history_lag_minutes\": 0,\n  \"toto_variant\": \"4m\",\n  \"history_cutoff_at\": \"2023-11-07T05:31:56Z\",\n  \"prediction_end_at\": \"2023-11-07T05:31:56Z\",\n  \"analysis_mode\": \"forecast\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://quantura.studio/api/v1/ensemble-forecasts")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"prediction_length\": 30,\n  \"quantiles\": [\n    123\n  ],\n  \"models\": {},\n  \"source\": {\n    \"type\": \"ticker\",\n    \"symbol\": \"<string>\",\n    \"price_side\": \"bid\",\n    \"start\": \"2023-12-25\",\n    \"limit\": 500,\n    \"frequency\": \"1Day\",\n    \"adjustment\": \"raw\",\n    \"session\": \"regular\"\n  },\n  \"transform\": \"auto\",\n  \"context_length\": 512,\n  \"model_failure_policy\": \"fail\",\n  \"frequency\": \"1D\",\n  \"calendar\": \"NYSE\",\n  \"workspace_id\": \"<string>\",\n  \"analytics_context\": {\n    \"analytics_consent\": \"granted\",\n    \"client_id\": \"<string>\",\n    \"session_id\": 123,\n    \"consent_at\": \"2023-11-07T05:31:56Z\"\n  },\n  \"history_lag_minutes\": 0,\n  \"toto_variant\": \"4m\",\n  \"history_cutoff_at\": \"2023-11-07T05:31:56Z\",\n  \"prediction_end_at\": \"2023-11-07T05:31:56Z\",\n  \"analysis_mode\": \"forecast\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://quantura.studio/api/v1/ensemble-forecasts")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"prediction_length\": 30,\n  \"quantiles\": [\n    123\n  ],\n  \"models\": {},\n  \"source\": {\n    \"type\": \"ticker\",\n    \"symbol\": \"<string>\",\n    \"price_side\": \"bid\",\n    \"start\": \"2023-12-25\",\n    \"limit\": 500,\n    \"frequency\": \"1Day\",\n    \"adjustment\": \"raw\",\n    \"session\": \"regular\"\n  },\n  \"transform\": \"auto\",\n  \"context_length\": 512,\n  \"model_failure_policy\": \"fail\",\n  \"frequency\": \"1D\",\n  \"calendar\": \"NYSE\",\n  \"workspace_id\": \"<string>\",\n  \"analytics_context\": {\n    \"analytics_consent\": \"granted\",\n    \"client_id\": \"<string>\",\n    \"session_id\": 123,\n    \"consent_at\": \"2023-11-07T05:31:56Z\"\n  },\n  \"history_lag_minutes\": 0,\n  \"toto_variant\": \"4m\",\n  \"history_cutoff_at\": \"2023-11-07T05:31:56Z\",\n  \"prediction_end_at\": \"2023-11-07T05:31:56Z\",\n  \"analysis_mode\": \"forecast\"\n}"

response = http.request(request)
puts response.read_body

{
  "data": {
    "forecast_id": "ens_01JEXAMPLE7M6N",
    "status": "queued",
    "progress": {
      "completed_models": 0,
      "total_models": 4,
      "current_model": null
    },
    "status_url": "/api/v1/ensemble-forecasts/ens_01JEXAMPLE7M6N",
    "result_url": "/api/v1/ensemble-forecasts/ens_01JEXAMPLE7M6N"
  },
  "meta": {
    "api_version": "v1"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "request_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  }
}

Backtests

Access

Workspaces

Datasets

Forecasts

Ensemble Forecasts

Screener

Kalshi Perpetuals

Q Support

Q Search

Q Download

Create an Asynchronous Multi-Model Quantura Forecast Job

Authorizations

Headers

Body

Response